Assesing carbon sequestration in brazilian northeastern biomes under ENSO events

Autores

  • Robson de Sousa Nascimento Universidade Federal da Paraíba
  • José Ivaldo Barbosa de Brito Universidade Federal de Campina Grande
  • Valéria Peixoto Borges Universidade Federal da Paraíba

DOI:

https://doi.org/10.22478/ufpb.1981-1268.2019v13n4.46299

Resumo

Net Primary Production (NPP) represents the amount of carbon absorbed by a plant. The present study aimed to know the behavior of the Net Primary Production (NPP) in years that have occurred El Niño Southern Oscillation (ENSO) and during the anomalies of the sea surface temperature (SST) in the Tropical Atlantic, that is Atlantic Dipole, to assessing the quantity of carbon absorbed by the northeastern biomes (Amazon Rainforest, Atlantic Forest, Cerrado and Caatinga) during these events. NPP was calculated using NDVI-AVHRR sensor data, and climate data from NCEP, both covering the period from 1981 to 1999. The results showed that the Amazon Rainforest, Atlantic Forest, and the Cerrado were not enough affected by the occurrence of ENSO and Atlantic Dipole. However, the Caatinga biome has shown to be quite sensitive to these events and patterns, especially in years of occurrence of El Niño, which contributed to a reduction in NPP; while in years of La Niña and negative dipole, the NPP achieved the highest values. The amount of precipitaton in previous year to the ENOS episodes showed influence on the amount of carbon sequestration by biomes in the year of study.

Downloads

Não há dados estatísticos.

Biografia do Autor

Robson de Sousa Nascimento, Universidade Federal da Paraíba

Centro de Ciências Agrárias - Departamento de Solos e Engenharia Rural

José Ivaldo Barbosa de Brito, Universidade Federal de Campina Grande

Centro de Tecnologia e Recursos Naturais - Unidade Acadêmica de Ciências Atmosféricas

Valéria Peixoto Borges, Universidade Federal da Paraíba

Centro de Ciências Agrárias - Departamento de Solos e Engenharia Rural

Referências

Alves EDL, Vecchia FAS. 2011. Análise de diferentes métodos de interpolação para a precipitação pluvial no Estado de Goiás. Acta Scientiarum, 33(2):193-197. http://dx.doi.org/10.4025/actascihumansoc.v33i2.13815.

Barbosa HA, Huete AR, Baethgen WE. 2006. A 20-year study of NDVI variability over the Northeast Region of Brazil. Journal of Arid Environments, 67(2):288-307. http://dx.doi.org/10.1016/j.jaridenv.2006.02.022.

Baret F, Olioso O. 1989. Estimation à partir de mesures de réflectance spectrale du rayonnement photosynthétiquement actif absorbé PAR une culture de blé. Agronomie; 9(9):885-895.

http://dx.doi.org/10.1051/agro:19890906.

Bastos A, Running S, Gouveia C, Trigo, RM. 2013. The global NPP dependence on ENSO: La Niña and the extraordinary year of 2011. Journal of Geophysical Research Biogeosciences, 118(3):1247–1255. http://dx.doi.org/10.1002/jgrg.20100.

Cao M, Zang Q, Shugart HH. 2001. Dynamic Responses of African Ecosystem Carbon Cycling to Climate Change. Climate Research, 17(2):183-193. http://dx.doi.org/10.3354/cr017183.

Cavalcanti IFA. 2012. Large scale and synoptic features associated with extreme precipitation over South America: A review and case studies for the first decade of the 21st century. Atmospheric Research, 118(15):27–40.

http://dx.doi.org/10.1016/j.atmosres.2012.06.012.

Chen B, Arain MA, Khomik M, Trofymow JA, Grant RF, Kurz WA et al. 2013. Evaluating the impacts of climate variability and disturbance regimes on the historic carbon budget of a forest landscape. Agricultural and Forest Meteorology, 180(10):265-280. http://dx.doi.org/10.1016/j.agrformet.2013.06.002.

Chino, DYT, Romani, LAS, Traina, AJM. 2010. Construindo séries temporais de imagens de satélite para sumarização de dados climáticos e monitoramento de safras agrícolas. Brasília:CNPTIA/EMBRAPA, 16 p.

Avaliable in https://ainfo.cnptia.embrapa.br/digital/bitstream/item/23611/1/REIC2010.pdf Access in 20/02/2018.

Climate Prediction Center (CPC) / National Oceanic and Atmospheric Administration (NOAA). Cold & Warm Episodes by Season. 2018. http://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php Access in 20/02/2018.

Costa MH, Nunes EL, Senna MCA, Imbuzeiro HMA. 2009. Estado-da-arte da simulação da taxa de fixação de carbono de ecossistemas tropicais. Revista Brasileira de Meteorologia, 24(2):179-187. http://dx.doi.org/10.1590/S0102-77862009000200007.

Costa WLB, Braga CC, Alcantara CR, Costa AS. 2017. Phenological Dynamics of Vegetation Using the Enhanced Vegetation Index (EVI) in Regions of Bahia State. Journal of Hyperspectral Remote Sensing,7(7):399-407. https://doi.org/10.29150/jhrs.v7i7.231391.

Crabtree R, Potter C, Mullen R, Sheldon J, Huang S, Harmsen J, Rodman A, Jean C. 2009. A modeling and spatio-temporal analysis framework for monitoring environmental change using NPP as an ecosystem indicator. Remote Sensing of Environment, 113(7):1486–1496. http://dx.doi.org/10.1016/j.rse.2008.12.014.

Fensholt R, Sandholt I, Rasmussen MS, Stisen S, Diouf A. 2006. Evaluation of satellite based primary production modeling in the semi-arid Sahel. Remote Sensing of Environment, 105(3):173-188. http://dx.doi.org/10.1016/j.rse.2006.06.011.

Ferreira WPM. 2006. Radiação Solar em Sete Lagoas – MG. Sete Lagoas: Embrapa, 21 p.

Ferreira AG, Mello NGS. 2005. Principais Sistemas Atmosféricos Atuantes sobre a Região Nordeste do Brasil e a Influência dos Oceanos Pacífico e Atlântico no Clima da Região. Revista Brasileira de Climatologia, 1(1): 15-28. http://dx.doi.org/10.5380/abclima.v1i1.

Gang C, Zhang Y, Wang Z et al. 2017. Modeling the dynamics of distribution, extent, and NPP of global terrestrial ecosystems in response to future climate change. Global and Planetary Change, 148:153–165. http://dx.doi.org/10.1016/j.gloplacha.2016.12.007.

Galvíncio JD, Sousa FAS. 2007. Avaliação do Desempenho de Modelo Hidrológico de Balanço Hídrico na Sub-bacia de Caraúbas, em anos de El Niño e La Niña. Revista Brasileira de Recursos Hídricos, 12(4):103-110. http://dx.doi.org/10.21168/rbrh.v12n4.p103-110.

Grace JH. 2005. Role of forest biomes in the global carbon balance. In: Griffiths H, Jarvis PG (Eds). The carbon balance of forest biomes. Edinburg: Taylor & Francis; p. 19-47.

Hashimoto H, Nemani RR, White MA, Jolly WM, Piper SC, Keeling CD et al. 2004. El Niño–Southern Oscillation–induced variability in terrestrial carbon cycling. Journal of Geophysical Research, 109(D23):1-8. http://dx.doi.org/10.1029/2004JD004959.

Hilker T, Hall FG, Coops NC, Lyapustin A, Wang Y, Nesic Z et al. 2010. Remote sensing of photosynthetic light-use efficiency across two forest biomes: Spatial scaling. Remote Sensing of Environment, 114(12):2863-2874. http://dx.doi.org/10.1016/j.rse.2010.07.004.

Hao R, Yu D, Wu J. 2017. Relationship between paired ecosystem services in the grassland and agro-pastoral transitional zone of China using the constraint line method. Agriculture, Ecosystems & Environment, 240:171-181. http://dx.doi.org/10.1016/j.agee.2017.02.015.

Instituto Brasileiro de Geografia e Estatística – IBGE. 2004. Accessed on 2015 aug. 05. Available from: http://www.ibge.gov.br/home/presidencia/noticias/21052004biomashtml.shtm.

Instituto Nacional de Meteorologia – INMET. Normais Climatológicas do Brasil período 1981 a 2010. Brasília:INMET, 2018. Availiable in http://www.inmet.gov.br/portal/index.php?r=clima/normaisClimatologicas. Accessed in 05/04/2018.

Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L et al. 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin American Meteorology Society, 77(3):437-471. http://dx.doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

Kayano MT, Andreoli RV. 2007. Relations of South American summer rainfall interannual variations with the Pacific decadal oscillation. International Journal of Climatology, 27(4):531-540. http://dx.doi.org/10.1002/joc.1417.

Kayano MT, Capistrano VB. 2014. How the Atlantic multidecadal oscillation (AMO) modifies the ENSO influence on the South American rainfall. International Journal of Climatology, 34:162–178. http://dx.doi.org/10.1002/joc.3674.

Kobayashi H, Dye DG. 2005. Atmospheric conditions for monitoring the long-term vegetation dynamics in the Amazon using normalized difference vegetation index. Remote Sensing of Environment, 97(4):519–525. http://dx.doi.org/10.1016/j.rse.2005.06.007.

Landau EC. Biomas da Região Nordeste do Brasil. 2013. [cited 2015 oct. 22]. Avaliable in:

http://panorama.cnpms.embrapa.br/mapas/geografia-do-milho-no-nordeste/mapa_aplmilho2009a11_biomas.jpg/view.

Li Z, Chen Y, Wang Y, Fang G. 2016. Dynamic changes in terrestrial net primary production and their effects on evapotranspiration. Hydrology and Earth System Science, 20:2169–2178. http://dx.doi.org/10.5194/hess-20-2169-2016.

Li P, Peng C, Wang M et al. 2017. Quantification of the response of global terrestrial net primary production to multifactor global change. Ecological Indicators, 76:245–255. http://dx.doi.org/10.1016/j.ecolind.2017.01.021.

Liang W, Yang Y, Fan D, Guan H, Zhang T, Long D, Zhou Y, Bai D. 2015. Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010. Agricultural and Forest Meteorology, 204:22–36.

http://dx.doi.org/10.1016/j.agrformet.2015.01.015.

Marcuzzo FFN, Goularte ERP. 2013. Caracterização do ano hidrológico e mapeamento espacial das chuvas nos períodos úmido e seco do estado do Tocantins. Revista Brasileira de Geografia Física, 6(1):91-99.

McCallum I, Wagner W, Schmullius C, Shvidenko A, Obersteiner, M, Fritz S et al. 2010. Comparison of four global fAPAR datasets over Northern Eurasia for the year 2000. Remote Sensing of Environment, 114(5):941-949. http://dx.doi.org/10.1016/j.rse.2009.12.009.

Menezes HEA, Brito JIB, Santos CAC, Silva LL. 2008. A relação entre a temperatura da superfície dos oceanos tropicais e a duração dos veranicos no Estado da Paraíba. Revista Brasileira de Meteorologia, 23(2):152-161. http://dx.doi.org/10.1590/S0102-77862008000200004.

Miranda E. Desafios e oportunidades para o desenvolvimento agropecuário e social nos Biomas do Nordeste Brasileiro. Brasília: Embrapa; 2010. Avaliable on https://www.embrapa.br/gite/projetos/nordeste/150408_NORDESTEMAPA.pdf. Accessed in 01/13/2019.

Morais, YCB, Araújo, MSB, Moura, MSB, Galvíncio, JD, Miranda, RQ. 2017. Análise do Sequestro de Carbono em Áreas de Caatinga do Semiárido Pernambucano. Revista Brasileira de Meteorologia, 32(4):585-599.

http://dx.doi.org/10.1590/0102-7786324007).

Moura AD, Shukla J. 1981. On the dynamics of the droughts in northeast Brazil: Observations, theory and numerical experiments with a general circulation model. Journal of the Atmospheric Science, 38(12): 2653-2673.

http://dx.doi.org/10.1175/1520-0469(1981)038<2653:OTDODI>2.0.CO;2.

Nascimento RS, Brito JIB, Borges VP, Borges PF, Araújo LS. 2017. Variabilidade interanual dos teores de carbono absorvido nos biomas nordestinos e sua relação com fatores climáticos. Gaia Scientia, 11(3):232-242.

http://dx.doi.org/10.21707/gs.v11.n03a17.

Pachavo G, Murwira A. 2014. Remote sensing net primary productivity (NPP) estimation with the aid of GIS modelled shortwave radiation (SWR) in a Southern African Savanna. International Journal of Applied Earth Observation and Geoinformation, 30(1):217-226.

http://dx.doi.org/10.1016/j.jag.2014.02.007.

Peng D, Zhang B, Wu C et al. 2017. Country-level net primary production distribution and response to drought and land cover change. Science of the Total Environment, 574:65–77.

http://dx.doi.org/10.1016/j.scitotenv.2016.09.033.

Potter C, Klooster S, Huete A, Genovese V, Bustamante M, Ferreira LG, Oliveira Jr RC, Zepp R. 2009. Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling. Biogeosciences, 6:937–945.

http://dx.doi.org/10.5194/bg-6-937-2009.

Saldarriaga JG, Luxmoore R. 1991. Solar energy conversion efficiencies during succession of a tropical rain forest in Amazonia. Journal of Tropical Ecology, 7(2):233-242.

http://dx.doi.org/10.1017/S0266467400005393.

Santos SRQ, Silva RBC, Barreto PN, Nunes HGGC, Rodrigues RS, Campos TLOB. 2011. Regime térmico e hídrico do solo para área de Floresta Tropical em anos de El Niño e La Niña, Caxiuanã-pa: estudo de caso. Revista Brasileira de Meteorologia, 26(3):367-374.

http://dx.doi.org/10.1590/S0102-77862011000300004.

Schwalm CR, Black TA, Amiro BD, Arain MA, Barr AG, Bourque CP et al. 2006. Photosynthetic light use efficiency of three biomes across an east–west continental-scale transect in Canada. Agricultural and Forest Meteorology, 140(1-4):269–286.

http://dx.doi.org/10.1016/j.agrformet.2006.06.010.

Silva MAO, Liporace FS. 2016. Detecção automática de nuvem e sombra de nuvem em imagens de sensoriamento remoto. Boletim de Ciências Geodésicas, 22(2):369-388.

http://dx.doi.org/10.1590/S0102-77862011000300004.

Silva PF, Lima JRS, Antonino ACD, Souza R, Souza ES, Silva RI, Alves EM. 2017. Seasonal patterns of carbon dioxide, water and energy fluxes over the Caatinga and grassland in the semi-arid region of Brazil. Journal of Arid Environments, 147:71-82.

http://dx.doi.org/10.1016/j.jaridenv.2017.09.003.

Wang Q, Zhao P, Ren H, Kakubari Y. 2008. Spatiotemporal dynamics of forest net primary production in China over the past two decades. Global and Planetary Change, 61(3-4):267–274.

http://dx.doi.org/10.1016/j.gloplacha.2006.12.007.

Wang X, Li F, Gao R, Luo Y, Liu T. 2014. Predicted NPP spatiotemporal variations in a semiarid steppe watershed for historical and trending climates. Journal of Arid Environment, 114(5): 67-79.

http://dx.doi.org/10.1016/j.jaridenv.2014.02.003.

Xu C, Liu M, An S, Chen JM, Yan P. 2007. Assessing the impact of urbanization on regional net primary productivity in Jiangyin County, China. Journal of Environmental Management, 85(3):597-606.

http://dx.doi.org/10.1016/j.jenvman.2006.08.015.

Yu B, Chen F. 2016. The global impact factors of net primary production in diferente land cover types from 2005 to 2011. SpringerPlus, 5:1235.

http://dx.doi.org/10.1186/s40064-016-2910-1.

Publicado

2019-12-30

Como Citar

NASCIMENTO, R. de S.; BRITO, J. I. B. de; BORGES, V. P. Assesing carbon sequestration in brazilian northeastern biomes under ENSO events. Gaia Scientia, [S. l.], v. 13, n. 4, 2019. DOI: 10.22478/ufpb.1981-1268.2019v13n4.46299. Disponível em: https://periodicos.ufpb.br/index.php/gaia/article/view/46299. Acesso em: 18 nov. 2024.

Edição

Seção

Ciências Ambientais

Artigos mais lidos pelo mesmo(s) autor(es)